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Improving automatic cyberbullying detection in social network environments by fine-tuning a pre-trained sentence transformer language model
The internet use among children and adolescents has increased massively recently. This situation has promoted harmful situations such as...
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Unveiling intrusions: explainable SVM approaches for addressing encrypted Wi-Fi traffic in UAV networks
Unmanned aerial vehicles (UAVs), also known as drones, have become instrumental in various domains, including agriculture, geographic information...
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Cooperative coati optimization algorithm with transfer functions for feature selection and knapsack problems
Coatis optimization algorithm (COA) has recently emerged as an innovative meta-heuristic algorithm (MA) for global optimization, garnering...
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Construction and application of medication reminder system: intelligent generation of universal medication schedule
BackgroundPatients with chronic conditions need multiple medications daily to manage their condition. However, most patients have poor compliance,...
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CLUSTERDC: A New Density-Based Clustering Algorithm and its Application in a Geological Material Characterization Workflow
The ore and waste materials extracted from a mineral deposit during the mining process can have significant variations in their physical and chemical...
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Text summarization based on semantic graphs: an abstract meaning representation graph-to-text deep learning approach
Nowadays, due to the constantly growing amount of textual information, automatic text summarization constitutes an important research area in natural...
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An Artificial Neural Network Approach for Predicting TOC and Comprehensive Pyrolysis Parameters from Well Logs and Applications to Source Rock Evaluation
Understanding source rocks' organic content and thermal maturity is crucial in assessing their hydrocarbon potential. To address this, our study...
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How clustering affects the convergence of decentralized optimization over networks: a Monte-Carlo-based approach
Decentralized algorithms have gained substantial interest owing to advancements in cloud computing, Internet of Things (IoT), intelligent...
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Failure analysis in smart grid solar integration using an extended decision-making-based FMEA model under uncertain environment
Failures in the integration of solar energy into smart grids can have significant implications for energy reliability and environmental...
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Quantifying the stochastic trends of climate extremes over Yemen: a comprehensive assessment using ERA5 data
Climate change is worsening existing vulnerabilities in develo** countries such as Yemen. This study examined the spatial distribution trends of...
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Forecasting short- and medium-term streamflow using stacked ensemble models and different meta-learners
Streamflow forecasting holds a pivotal role in the effective management of water resources, flood control, hydropower generation, agricultural...
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DQMMBSC: design of an augmented deep Q-learning model for mining optimisation in IIoT via hybrid-bioinspired blockchain shards and contextual consensus
Single-chained blockchains are highly secure but cannot be scaled to larger IIoT (Internet of Industrial Things) network scenarios due to storage...
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SsL-VGMM: A Semisupervised Machine Learning Model of Multisource Data Fusion for Lithology Prediction
In deep mineral exploration, it is difficult to constrain the complex geological structures using a single geophysical method. To tackle the...
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Effects of Different Concentrations of Weak Acid Fracturing Fluid on the Microstructure of Coal
As a crucial factor that influences the hydraulic fracturing effectiveness of coal seams, fracturing fluids have garnered increasing attention. Among...
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Impact of climate and weather extremes on soybean and wheat yield using machine learning approach
The escalating climate instability and extreme weather events significantly jeopardize food security. The study assessed the impact of long-term...
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Enhancing OCT patch-based segmentation with improved GAN data augmentation and semi-supervised learning
For optimum performance, deep learning methods, such as those applied for retinal and choroidal layer segmentation in optical coherence tomography...
